Our project is relevant to the RC4 areas of "Applying Genomics and Other High Throughput Technologies" and to "Using Science to Enable Health Care Reform." We will comprehensively interrogate how genomic variation affects outcome, coupled with an integrated analysis of large clinical datasets, to understand how polymorphisms that are related to ancestral background affect acute lymphoblastic leukemia (ALL) relapse risk. The project is ready to go and can be analyzed within the time frame of the application;new hires are consistent with the goals of ARRA;using the existing infrastructure of the COG and St. Jude, the project is sustainable beyond the period of funding. ALL serves as a model for drug-responsive tumors: cure rates approach ~85%, but the cost of these high cure rates involves common serious adverse reactions to medications. This is a disease in which pharmacogenomic testing may allow for individualization of medications to further improve cure rates and minimize adverse drug effects. ALL is also a model for the study of racial and ethnic disparities in health outcomes. Patients of Hispanic ethnicity have a higher risk of relapse than other race groups. Our group has recently shown that there is a genomic component to this higher relapse rate in Hispanics, and this disparity in outcome appears to be abrogated by certain therapies. The gap in our knowledge is that we do not yet know the genomic mechanisms that underlie these racial/ethnic disparities, nor is it defined whether these disparities are present in the most modern ALL regimens. In this application, we capitalize on the most recent Children's Oncology Group (COG) phase III clinical trials, and test the hypothesis that ancestry-related genetic variation contributes to racial disparities in treatment outcome of ALL, partly through modulating response to and disposition of anti-leukemic agents. In Aim 1, we will determine the contribution of global genetic ancestral composition to relapse risk in ALL, and the impact of randomized treatment interventions on that contribution, studying the ~ 2500 patients already enrolled on the COG AALL0232 trial for high risk ALL. We will use genomic tools to study the major genetic ancestral groups of the U.S. population and assess the impact of two treatment randomizations. In Aim 2, we will use admixture mapping to identify which specific germ-line genetic variations contribute to racial/ethnic disparities in outcome of ALL. In Aim 3, we will assess whether genomic ancestry associated with ancestry-related relapse risk is associated with anti-leukemic drug exposure (drug disposition and adherence) in a COG trial (AALL03N1, n ~ 720) that has been specifically designed to assess the contribution of race and ethnicity to these phenotypes, and identify which polymorphisms contribute to racial differences in outcome via influencing thiopurine exposure. The eventual goal will be to implement pharmacogenomic testing to tailor medications to eliminate racial disparities in ALL outcomes and to mitigate the risk of relapse, a strategy that the COG and St. Jude have already used in past trials. These findings have applicability for use of similar drugs in adult malignancies and in non-cancer conditions. PUBLIC HEALTH RELEVANCE: For some diseases, there are differences among racial/ethnic groups in cure rates. With the new tools of genomics, we propose to identify the extent to which genomic variation explains the differences among race/ethnicity groups in cure rates for childhood leukemia, what genes are involved, and whether those gene variations explain differences among race/ethnic groups in exposure to anti-leukemic medications. Long term, we aim to eradicate race/ethnicity differences in cure rates.